Protocol for detecting intracellular aggregations in Arabidopsis thaliana cell wall mutants using FM4-64 staining
Bibliographic record
Abstract
Here, we present a step-by step protocol to visualize intracellular aggregations in Arabidopsis mutants with cell wall secretion defects using FM4-64, a lipophilic styryl dye. We describe steps for growing seedlings, staining them with FM4-64, and identifying intracellular aggregates in cell wall synthesis and/or secretion mutants in root and hypocotyl epidermal cells via confocal microscopy. Additionally, we provide troubleshooting suggestions for common pitfalls. For complete details on the use and execution of this protocol, please refer to Hoffmann and McFarlane. 1 • Protocol to detect intracellular aggregates in Arabidopsis cell wall synthesis/secretion mutants • Instructions for staining and imaging aggregations in live root or hypocotyl cells • Guidance and troubleshooting on distinguishing aggregations from common artifacts Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics. Here, we present a step-by step protocol to visualize intracellular aggregations in Arabidopsis mutants with cell wall secretion defects using FM4-64, a lipophilic styryl dye. We describe steps for growing seedlings, staining them with FM4-64, and identifying intracellular aggregates in cell wall synthesis and/or secretion mutants in root and hypocotyl epidermal cells via confocal microscopy. Additionally, we provide troubleshooting suggestions for common pitfalls.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.031 | 0.018 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".